Staff Data Engineer, Data Platform - IntelliScript

Accountabilities

• Act as a subject matter expert and thought leader for the Data Platform domain, providing technical guidance and influencing architecture and engineering decisions.
• Define and advance data engineering strategy, including approaches for moving, storing, processing, governing, and maintaining high-quality enterprise data.
• Lead complex data platform initiatives by coordinating teams, managing timelines, communicating progress, and aligning technical execution with strategic business objectives.
• Expand and optimize enterprise data warehouses and lakehouse environments supporting healthcare-focused data products and internal use cases.
• Establish and maintain data governance capabilities, including Unity Catalog configuration, data lineage, data quality, auditability, stewardship, and compliance with evolving industry standards.
• Design and implement data security practices for identified and de-identified PHI and PII, consistently applying least-privilege access principles.
• Build reliable external data products that meet high standards for data quality, performance, scalability, security, and operational reliability.
• Develop ETL and transformation solutions using Delta Live Tables, automation, SQL, Python, Scala, and cloud-based big data technologies.
• Design performant enterprise medallion architectures and fit-for-purpose batch and near-real-time streaming solutions.
• Architect solutions for large, diverse structured and unstructured healthcare datasets used by both internal and external stakeholders.
• Build platform infrastructure using Infrastructure as Code practices, including Terraform, Asset Bundles, and GitHub-based development workflows.
• Partner with business stakeholders to design cost-effective and transparent data solutions while balancing performance, scalability, security, and operational requirements.
• Architect, build, maintain, monitor, and optimize scalable data pipelines and ETL infrastructure across diverse data sources.
• Work with migration and integration technologies such as Fivetran, AWS services, and custom data ingestion solutions.
• Design reliable event-driven data processing and effective pipeline monitoring capabilities to improve resilience and operational visibility.
• Design and implement internal APIs that enable data integration across systems and applications.
• Develop APIs that allow internal systems to consume datasets and capabilities from Databricks, while integrating with external platforms such as Salesforce, financial systems, HR systems, and other business applications.
• Lead the design, implementation, and maintenance of standards-based data models for structured and unstructured data, including healthcare standards such as FHIR and OMOP.
• Assemble complex datasets that satisfy functional and non-functional requirements while ensuring models align with business objectives and data privacy regulations.
• Collaborate with data engineering, software development, analytics, data science, clinical, and business teams to gather requirements and deliver meaningful data solutions.
• Translate complex technical concepts into clear guidance for non-technical stakeholders and advise teams on appropriate data engineering and architectural practices.
• Develop project plans, estimate implementation efforts, and ensure technology execution remains aligned with business strategy.
• Identify and implement process improvements through automation, infrastructure redesign, optimized data delivery, and scalable engineering practices.
• Build analytics and data tools that provide actionable insights into operational performance and support clinical, analytics, and data science teams.
• Evaluate emerging technologies, investigate new tooling, develop implementation plans, and lead the deployment of solutions that improve platform capabilities.
• Mentor and guide engineers on emerging technologies while leading through influence, technical expertise, and strategic collaboration.

Requirements

• At least 15 years of relevant experience designing, developing, and testing enterprise Data Platform solutions, including data warehouses, data lakes, and data products.
• Expert-level experience with Databricks and AWS.
• Expert knowledge of relational and non-relational databases, including technologies such as SQL Server, PostgreSQL, DynamoDB, and DocumentDB.
• Demonstrated experience managing and standardizing clinical data from both structured and unstructured sources.
• Extensive experience building, deploying, and managing data solutions within AWS environments.
• Expert knowledge of healthcare data standards, including FHIR, C-CDA, and traditional HL7.
• Expert knowledge of clinical standards and ontologies such as ICD-10, SNOMED, NDC, LOINC, and RxNorm.
• Expert capability in data modeling, enterprise data warehouse architecture, data lake design, and data product development.
• Strong experience designing and building APIs, ETL frameworks, data ingestion processes, and supporting enterprise data solutions.
• Experience with performance tuning, query optimization, data security, monitoring, and release management.
• Proven ability to work with large, disparate datasets, including identified and de-identified healthcare data from multiple sources.
• Experience implementing Infrastructure as Code using Terraform, Asset Bundles, and GitHub.
• Experience collaborating with Data Science teams and developing or supporting AI-based solutions that generate operational efficiencies and business value.
• Strong communication and collaboration skills across technical and non-technical disciplines.
• Ability to navigate ambiguity, identify practical solutions, and balance strategic priorities with tactical execution.
• Demonstrated ability to teach, mentor, and influence engineering teams on new and emerging technologies.
• Customer-focused and business-oriented approach, with the ability to connect technical decisions to measurable organizational outcomes.
• Self-directed, thorough, driven, and comfortable taking ownership of complex technical initiatives.
• Strong influencing and persuasion skills, with the ability to lead without relying solely on formal authority.
• Curiosity about emerging industry trends and a commitment to selecting fit-for-purpose technologies and approaches.
• Bachelor’s or master’s degree in Computer Science, Data Engineering, or a related field is preferred.
• Experience within the health insurance or life insurance industry is preferred.
• Professional-level AWS solution architecture certification is a plus.
• Willingness to travel to a company office in Brookfield, Wisconsin, as needed, as well as travel nationally for meetings, conferences, and team events.

Benefits

• Annual salary range of $131,600 to $249,780, depending on qualifications, experience, location, skills, certifications, and other relevant factors.
• For candidates residing in Alaska, California, Connecticut, Illinois, Maryland, Massachusetts, New Jersey, New York City, Pennsylvania, Virginia, Washington, or Washington, D.C., the salary range is $151,340 to $249,780.
• For candidates in other U.S. locations, the salary range is $131,600 to $217,200.
• Remote work opportunity available anywhere in the United States.
• Medical, dental, and vision coverage for employees, dependents, and domestic partners.
• Employee Assistance Program providing confidential personal and work-related support.
• 401(k) plan with company matching and profit-sharing contributions.
• Discretionary bonus program recognizing employee contributions.
• Flexible Spending Accounts for eligible medical, dependent care, transportation, and other qualified expenses.
• Paid time off beginning on the first day of employment, with full-time employees accruing 15 days annually.
• At least 10 paid holidays per year.
• Family-building benefits, including adoption and fertility assistance.
• Up to 11 weeks of paid parental leave for eligible employees.
• Employer-paid life insurance and AD&D coverage.
• Employer-paid short-term and long-term disability coverage.
• Access to learning, mentoring, professional development, and skills training opportunities.
• Opportunity to influence enterprise data strategy and work with modern cloud, lakehouse, AI, and healthcare data technologies.
• High-impact technical leadership role with significant autonomy, cross-functional exposure, and opportunities to mentor and influence engineering teams.